Scholarlink

<p>In this paper we propose a new scaling method to study the Schur complements of locally doubly strictly diagonally dominant (for shortly, LDSDD) matrices. Compared with the previous methods, the proposed method can obtain a more accurate numerical estimate in a more succinctly manner. Based on the Schur complement, a new upper bound of the infinity norm for the inverse of LDSDD matrices is presented. We apply the new bound to derive an error bound for linear complementarity problems of <i>LB</i>-matrices. Many numerical experiments with lots of random matrices are presented to show the efficiency and superiority of our results.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

On Schur complements of locally doubly strictly diagonally dominant matrices and its applications

  • 期刊论文

  • 发表日期：

    2025年8月14日

查看全文
  • Yang Hu,
  • Jianzhou Liu,
  • Yebo Xiong,
  • Wenlong Zeng

摘要

In this paper we propose a new scaling method to study the Schur complements of locally doubly strictly diagonally dominant (for shortly, LDSDD) matrices. Compared with the previous methods, the proposed method can obtain a more accurate numerical estimate in a more succinctly manner. Based on the Schur complement, a new upper bound of the infinity norm for the inverse of LDSDD matrices is presented. We apply the new bound to derive an error bound for linear complementarity problems of LB-matrices. Many numerical experiments with lots of random matrices are presented to show the efficiency and superiority of our results.